The field of the disclosure relates generally to spatial filtering of signal data received by wide-area surveillance sensors, and, more specifically, to systems and methods for adding functional grid elements to stochastic sparse tree grids for spatial filtering.
In known spatial filtering systems and methods, improved pre-processing front-end architectures generate signal data vectors having new characteristics and require more extensive processing systems and methods. Improvements in known spatial filtering systems and methods including denoising and blind source separation generate signal parameter vectors containing new characteristics and additional new information types. In order to efficiently generate useful deinterleaving information of signal parameter vectors during post-processing, such known spatial filtering systems and methods require substantially more complex processor architectures. Even with improved post-processing architectures, such known spatial filtering systems and methods suffer from diminished deinterleaving performance with new types of signal parameter vector data and non-standard data relative to standard signal parameter vectors.
At least some known spatial filtering and signal parameter vector deinterleaving systems and methods are challenging to implement in a single platform architecture which can only produce angle of arrival (AOA) spatial information, rather than a more exact spatial location. Further, at least some known spatial filtering and signal parameter vector deinterleaving systems and methods are unable, absent highly sophisticated, complex, and expensive post-processing computing requirements, to combine non-standard signal parameters having widely varying accuracies and employ moving emitter platform spatial signal parameters as part of signal parameter vector deinterleaving. Finally, when stochastic histogram methods are used to spread out spatial data in a grid with very small cells for the purpose of generating accurate results, in at least some known spatial filtering systems and methods, use of a standard post-processing architecture is unacceptably inefficient.